Advancing Business Performance Through Artificial Intelligence: The Interplay of Digital Competence, Innovation, and Operational Efficiency

Agustian Agustian () and Indrianty Sudirman
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Agustian Agustian: Hasanuddin University
Indrianty Sudirman: Hasanuddin University

A chapter in Proceedings of the 10th International Conference on Accounting, Management, and Economics (10th ICAME 2025), 2026, pp 81-98 from Springer

Abstract: Abstract This study investigates the relationship between Digital Competence (DC), Innovation (I), Operational Efficiency (OE), and Organizational Performance (OP) within the context of Artificial Intelligence (AI) adoption. As AI continues to transform industries, understanding how digital competence, innovation, and operational efficiency interact to enhance organizational performance becomes crucial for businesses striving to gain a competitive edge. A quantitative approach was adopted, utilizing surveys distributed to managers in manufacturing companies in Makassar and Gowa, Indonesia. The findings reveal that digital competence has a strong positive impact on organizational performance (p = 0.001), indicating its central role in driving performance improvements. Innovation also positively influences organizational performance (p = 0.000), although to a lesser extent than digital competence. Operational efficiency further contributes significantly to organizational performance (p = 0.001), demonstrating that improved processes and resource management lead to better business outcomes. The study underscores the importance of integrating AI within an organization’s digital transformation strategy, highlighting the need for continuous development of digital skills, fostering innovation, and optimizing operational processes. These insights provide valuable guidance for organizations aiming to enhance their performance through AI adoption and digital transformation.

Keywords: Artificial Intelligence; Digital Competence; Innovation; Operational Efficiency; Organizational Performance (search for similar items in EconPapers)
Date: 2026
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DOI: 10.2991/978-94-6239-709-5_7

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